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Spatial Dependencies between Large-Scale Brain Networks
Functional neuroimaging reveals both increases (task-positive) and decreases (task-negative) in neural activation with many tasks. Many studies show a temporal relationship between task positive and task negative networks that is important for efficient cognitive functioning. Here we provide evidenc...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4041825/ https://www.ncbi.nlm.nih.gov/pubmed/24887067 http://dx.doi.org/10.1371/journal.pone.0098500 |
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author | Leech, Robert Scott, Gregory Carhart-Harris, Robin Turkheimer, Federico Taylor-Robinson, Simon D. Sharp, David J. |
author_facet | Leech, Robert Scott, Gregory Carhart-Harris, Robin Turkheimer, Federico Taylor-Robinson, Simon D. Sharp, David J. |
author_sort | Leech, Robert |
collection | PubMed |
description | Functional neuroimaging reveals both increases (task-positive) and decreases (task-negative) in neural activation with many tasks. Many studies show a temporal relationship between task positive and task negative networks that is important for efficient cognitive functioning. Here we provide evidence for a spatial relationship between task positive and negative networks. There are strong spatial similarities between many reported task negative brain networks, termed the default mode network, which is typically assumed to be a spatially fixed network. However, this is not the case. The spatial structure of the DMN varies depending on what specific task is being performed. We test whether there is a fundamental spatial relationship between task positive and negative networks. Specifically, we hypothesize that the distance between task positive and negative voxels is consistent despite different spatial patterns of activation and deactivation evoked by different cognitive tasks. We show significantly reduced variability in the distance between within-condition task positive and task negative voxels than across-condition distances for four different sensory, motor and cognitive tasks - implying that deactivation patterns are spatially dependent on activation patterns (and vice versa), and that both are modulated by specific task demands. We also show a similar relationship between positively and negatively correlated networks from a third ‘rest’ dataset, in the absence of a specific task. We propose that this spatial relationship may be the macroscopic analogue of microscopic neuronal organization reported in sensory cortical systems, and that this organization may reflect homeostatic plasticity necessary for efficient brain function. |
format | Online Article Text |
id | pubmed-4041825 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-40418252014-06-09 Spatial Dependencies between Large-Scale Brain Networks Leech, Robert Scott, Gregory Carhart-Harris, Robin Turkheimer, Federico Taylor-Robinson, Simon D. Sharp, David J. PLoS One Research Article Functional neuroimaging reveals both increases (task-positive) and decreases (task-negative) in neural activation with many tasks. Many studies show a temporal relationship between task positive and task negative networks that is important for efficient cognitive functioning. Here we provide evidence for a spatial relationship between task positive and negative networks. There are strong spatial similarities between many reported task negative brain networks, termed the default mode network, which is typically assumed to be a spatially fixed network. However, this is not the case. The spatial structure of the DMN varies depending on what specific task is being performed. We test whether there is a fundamental spatial relationship between task positive and negative networks. Specifically, we hypothesize that the distance between task positive and negative voxels is consistent despite different spatial patterns of activation and deactivation evoked by different cognitive tasks. We show significantly reduced variability in the distance between within-condition task positive and task negative voxels than across-condition distances for four different sensory, motor and cognitive tasks - implying that deactivation patterns are spatially dependent on activation patterns (and vice versa), and that both are modulated by specific task demands. We also show a similar relationship between positively and negatively correlated networks from a third ‘rest’ dataset, in the absence of a specific task. We propose that this spatial relationship may be the macroscopic analogue of microscopic neuronal organization reported in sensory cortical systems, and that this organization may reflect homeostatic plasticity necessary for efficient brain function. Public Library of Science 2014-06-02 /pmc/articles/PMC4041825/ /pubmed/24887067 http://dx.doi.org/10.1371/journal.pone.0098500 Text en © 2014 Leech et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Leech, Robert Scott, Gregory Carhart-Harris, Robin Turkheimer, Federico Taylor-Robinson, Simon D. Sharp, David J. Spatial Dependencies between Large-Scale Brain Networks |
title | Spatial Dependencies between Large-Scale Brain Networks |
title_full | Spatial Dependencies between Large-Scale Brain Networks |
title_fullStr | Spatial Dependencies between Large-Scale Brain Networks |
title_full_unstemmed | Spatial Dependencies between Large-Scale Brain Networks |
title_short | Spatial Dependencies between Large-Scale Brain Networks |
title_sort | spatial dependencies between large-scale brain networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4041825/ https://www.ncbi.nlm.nih.gov/pubmed/24887067 http://dx.doi.org/10.1371/journal.pone.0098500 |
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